Real Estate and Rental and Leasing vs. Transportation and Warehousing
Earnings Structure and Growth by County
Texas, 2001-2022
Earnings by County
Percent of Total Earnings, 2022
Select a Year/Indicator:Percent of Total
Earnings
Location
Quotients
Percent of Sector Total
Statewide
Earnings by County
View Distribution Totals as:Actual Percent
   
 
Real Estate and Rental and Leasing vs. Transportation and Warehousing
Texas Earnings Distribution by County:
Percent of Total Earnings, 2022
More
than
3.5%
3.5%
to
3.0%
3.0%
to
2.5%
2.5%
to
2.0%
2.0%
to
1.5%
1.5%
to
1.0%
1.0%
to
0.5%
0.5%
or
Below
Total
Real Estate and Rental and Leasing
27
12
18
26
35
37
26
73
254
Transportation and Warehousing
121
14
16
12
11
12
4
64
254
 
   
Select an alternate year:
   
 
Real Estate and Rental and Leasing vs. Transportation and Warehousing
Earnings Structure by County:
Texas, 2022
 
Real Estate and Rental and Leasing
 
Transportation and Warehousing
 
 
 
23,403
1.5
0.6
0.1
 
215,334
13.6
3.2
0.3
 
19,140
2.5
1.0
0.1
 
46,759
6.1
1.5
0.1
 
27,875
1.2
0.5
0.1
 
92,781
3.8
0.9
0.1
 
29,854
6.0
2.3
0.1
 
25,704
5.2
1.2
0.0
 
S
S
U
S
 
7,116
4.1
1.0
0.0
 
S
S
U
S
 
S
S
U
S
 
34,897
3.0
1.2
0.1
 
94,479
8.2
2.0
0.1
 
35,623
3.3
1.3
0.1
 
69,511
6.5
1.5
0.1
 
S
S
U
S
 
13,318
6.0
1.4
0.0
 
2,267
0.8
0.3
0.0
 
11,878
4.4
1.0
0.0
 
24,244
1.4
0.5
0.1
 
53,959
3.0
0.7
0.1
 
S
S
U
S
 
S
S
U
S
 
11,217
2.4
0.9
0.0
 
7,480
1.6
0.4
0.0
 
310,369
2.2
0.9
1.1
 
389,172
2.7
0.7
0.5
 
1,297,081
1.6
0.6
4.5
 
3,285,157
4.0
0.9
4.3
 
12,501
3.5
1.4
0.0
 
17,815
5.0
1.2
0.0
 
241
0.6
0.2
0.0
 
S
S
U
S
 
6,358
2.2
0.9
0.0
 
10,983
3.8
0.9
0.0
 
41,829
1.4
0.6
0.1
 
109,967
3.8
0.9
0.1
 
244,990
2.2
0.9
0.9
 
387,222
3.5
0.8
0.5
 
216,562
2.6
1.0
0.8
 
S
S
U
S
 
3,267
1.1
0.4
0.0
 
2,927
1.0
0.2
0.0
 
109
0.3
0.1
0.0
 
226
0.6
0.1
0.0
 
S
S
U
S
 
5,493
3.1
0.7
0.0
 
16,383
1.6
0.6
0.1
 
24,098
2.4
0.6
0.0
 
5,458
1.6
0.6
0.0
 
31,265
8.9
2.1
0.0
 
68,341
4.7
1.8
0.2
 
S
S
U
S
 
16,090
2.1
0.8
0.1
 
75,704
9.9
2.4
0.1
 
16,512
1.1
0.4
0.1
 
29,393
1.9
0.4
0.0
 
11,050
5.1
2.0
0.0
 
12,482
5.7
1.4
0.0
 
201,777
2.2
0.8
0.7
 
520,037
5.5
1.3
0.7
 
10,448
3.6
1.4
0.0
 
6,935
2.4
0.6
0.0
 
573
0.1
0.0
0.0
 
7,334
1.2
0.3
0.0
 
8,576
1.6
0.6
0.0
 
25,363
4.7
1.1
0.0
 
7,095
1.6
0.6
0.0
 
18,067
4.0
1.0
0.0
 
26,404
1.4
0.6
0.1
 
264,539
14.3
3.4
0.3
 
14,205
1.5
0.6
0.0
 
19,305
2.0
0.5
0.0
 
1,902
0.9
0.4
0.0
 
S
S
U
S
 
S
S
U
S
 
S
S
U
S
 
99
0.2
0.1
0.0
 
S
S
U
S
 
S
S
U
S
 
1,136
1.6
0.4
0.0
 
9,505
6.2
2.4
0.0
 
S
S
U
S
 
1,042,856
1.7
0.7
3.7
 
603,794
1.0
0.2
0.8
 
S
S
U
S
 
S
S
U
S
 
12,323
2.3
0.9
0.0
 
39,458
7.4
1.8
0.1
 
183,495
3.2
1.3
0.6
 
304,464
5.4
1.3
0.4
 
3,914
1.2
0.5
0.0
 
25,881
7.8
1.9
0.0
 
109
0.2
0.1
0.0
 
S
S
U
S
 
67,132
4.8
1.9
0.2
 
45,205
3.2
0.8
0.1
 
29,079
2.6
1.0
0.1
 
18,761
1.7
0.4
0.0
 
603
0.8
0.3
0.0
 
5,191
7.3
1.7
0.0
 
8,447
6.4
2.5
0.0
 
15,744
11.9
2.8
0.0
 
558
0.6
0.2
0.0
 
15,859
16.3
3.9
0.0
 
S
S
U
S
 
S
S
U
S
 
7
0.0
0.0
0.0
 
1,627
1.1
0.3
0.0
 
6,023
1.3
0.5
0.0
 
S
S
U
S
 
6,931,587
3.0
1.2
24.3
 
11,803,073
5.2
1.2
15.4
 
2,505
0.7
0.3
0.0
 
6,813
2.0
0.5
0.0
 
2,290
0.2
0.1
0.0
 
35,387
3.7
0.9
0.0
 
S
S
U
S
 
S
S
U
S
 
478,155
1.8
0.7
1.7
 
1,820,412
6.7
1.6
2.4
 
35,779
6.8
2.7
0.1
 
31,598
6.0
1.4
0.0
 
122
0.4
0.2
0.0
 
561
1.9
0.4
0.0
 
12,619
2.5
1.0
0.0
 
19,789
4.0
0.9
0.0
 
S
S
U
S
 
2,156
3.6
0.9
0.0
 
358
0.2
0.1
0.0
 
14,763
7.6
1.8
0.0
 
10,680
2.2
0.9
0.0
 
29,654
6.2
1.5
0.0
 
209,310
2.9
1.1
0.7
 
490,182
6.8
1.6
0.6
 
S
S
U
S
 
S
S
U
S
 
56,109
1.2
0.5
0.2
 
390,149
8.6
2.1
0.5
 
394,254
1.6
0.6
1.4
 
1,590,891
6.3
1.5
2.1
 
30,606
2.4
0.9
0.1
 
46,574
3.6
0.9
0.1
 
S
S
U
S
 
S
S
U
S
 
11,192
1.9
0.8
0.0
 
15,544
2.7
0.6
0.0
 
22,052
3.6
1.4
0.1
 
S
S
U
S
 
S
S
U
S
 
4,210
6.2
1.5
0.0
 
S
S
U
S
 
4,959
4.8
1.1
0.0
 
54
0.2
0.1
0.0
 
S
S
U
S
 
281,548
1.3
0.5
1.0
 
860,581
4.0
0.9
1.1
 
S
S
U
S
 
65,647
18.4
4.4
0.1
 
6,602
1.8
0.7
0.0
 
32,375
8.9
2.1
0.0
 
10,213
1.8
0.7
0.0
 
27,214
4.9
1.2
0.0
 
8,460
1.1
0.4
0.0
 
61,485
8.0
1.9
0.1
 
150,126
1.5
0.6
0.5
 
317,526
3.2
0.8
0.4
 
540
0.5
0.2
0.0
 
6,343
6.1
1.5
0.0
 
73,607
8.1
3.2
0.3
 
S
S
U
S
 
S
S
U
S
 
S
S
U
S
 
1,884
2.1
0.8
0.0
 
S
S
U
S
 
2,679
0.3
0.1
0.0
 
28,444
3.6
0.9
0.0
 
9,137
1.5
0.6
0.0
 
19,944
3.3
0.8
0.0
 
40,086
1.1
0.4
0.1
 
104,375
2.9
0.7
0.1
 
203,737
3.5
1.4
0.7
 
271,816
4.6
1.1
0.4
 
24,700
4.1
1.6
0.1
 
28,598
4.7
1.1
0.0
 
134,725
3.6
1.4
0.5
 
285,089
7.7
1.8
0.4
 
12,530
1.6
0.6
0.0
 
109,336
13.5
3.2
0.1
 
358
0.9
0.3
0.0
 
S
S
U
S
 
1,912
1.0
0.4
0.0
 
S
S
U
S
 
796
0.3
0.1
0.0
 
10,295
3.4
0.8
0.0
 
S
S
U
S
 
4,619
4.4
1.0
0.0
 
9,276
1.1
0.4
0.0
 
32,261
3.7
0.9
0.0
 
5,771,329
1.9
0.7
20.2
 
25,746,149
8.5
2.0
33.7
 
43,391
2.3
0.9
0.2
 
49,441
2.6
0.6
0.1
 
S
S
U
S
 
16,429
4.2
1.0
0.0
 
288
0.2
0.1
0.0
 
3,196
2.3
0.5
0.0
 
248,920
3.5
1.4
0.9
 
503,788
7.1
1.7
0.7
 
2,864
1.7
0.7
0.0
 
S
S
U
S
 
25,684
1.9
0.8
0.1
 
35,542
2.7
0.6
0.0
 
346,120
1.9
0.8
1.2
 
1,053,512
5.9
1.4
1.4
 
13,472
1.6
0.6
0.0
 
45,180
5.5
1.3
0.1
 
15,933
2.0
0.8
0.1
 
38,173
4.8
1.1
0.0
 
59,162
4.3
1.7
0.2
 
25,908
1.9
0.5
0.0
 
14,908
1.3
0.5
0.1
 
51,666
4.5
1.1
0.1
 
9,522
1.6
0.6
0.0
 
S
S
U
S
 
14,425
1.4
0.5
0.1
 
20,230
1.9
0.5
0.0
 
80
0.1
0.0
0.0
 
S
S
U
S
 
24,771
1.0
0.4
0.1
 
47,062
2.0
0.5
0.1
 
6,609
0.9
0.4
0.0
 
21,661
3.0
0.7
0.0
 
S
S
U
S
 
2,821
3.3
0.8
0.0
 
S
S
U
S
 
10,473
4.7
1.1
0.0
 
3,356
0.9
0.3
0.0
 
S
S
U
S
 
13,040
2.1
0.8
0.0
 
S
S
U
S
 
S
S
U
S
 
578
1.2
0.3
0.0
 
138,090
1.3
0.5
0.5
 
387,184
3.8
0.9
0.5
 
S
S
U
S
 
S
S
U
S
 
27,115
2.8
1.1
0.1
 
23,973
2.5
0.6
0.0
 
110,884
2.6
1.0
0.4
 
269,892
6.3
1.5
0.4
 
2,769
0.9
0.3
0.0
 
13,664
4.3
1.0
0.0
 
13,594
2.7
1.1
0.0
 
33,254
6.6
1.6
0.0
 
36,605
1.2
0.5
0.1
 
447,364
15.2
3.6
0.6
 
78,796
4.4
1.7
0.3
 
S
S
U
S
 
44
0.1
0.0
0.0
 
45
0.1
0.0
0.0
 
S
S
U
S
 
329
1.0
0.2
0.0
 
105,587
6.6
2.6
0.4
 
16,705
1.0
0.2
0.0
 
2,665
3.1
1.2
0.0
 
S
S
U
S
 
122
0.5
0.2
0.0
 
7
0.0
0.0
0.0
 
S
S
U
S
 
S
S
U
S
 
7,551
0.9
0.4
0.0
 
10,549
1.3
0.3
0.0
 
S
S
U
S
 
S
S
U
S
 
9,793
0.6
0.2
0.0
 
46,842
2.8
0.7
0.1
 
4,018
0.9
0.3
0.0
 
13,244
2.9
0.7
0.0
 
15,101
4.1
1.6
0.1
 
S
S
U
S
 
S
S
U
S
 
13,388
4.3
1.0
0.0
 
14,415
3.0
1.2
0.1
 
S
S
U
S
 
9,127
1.6
0.6
0.0
 
S
S
U
S
 
18,579
3.8
1.5
0.1
 
13,124
2.7
0.6
0.0
 
32,282
2.2
0.9
0.1
 
123,397
8.5
2.0
0.2
 
1,479
0.3
0.1
0.0
 
7,840
1.4
0.3
0.0
 
S
S
U
S
 
36,403
12.8
3.1
0.0
 
25,477
8.4
3.3
0.1
 
30,597
10.1
2.4
0.0
 
28,797
6.9
2.7
0.1
 
S
S
U
S
 
5
0.0
0.0
0.0
 
S
S
U
S
 
170,384
1.6
0.6
0.6
 
376,427
3.5
0.8
0.5
 
S
S
U
S
 
3,567
2.2
0.5
0.0
 
2,543
1.6
0.6
0.0
 
S
S
U
S
 
281,191
2.9
1.1
1.0
 
294,321
3.1
0.7
0.4
 
S
S
U
S
 
S
S
U
S
 
3,431
1.2
0.5
0.0
 
S
S
U
S
 
S
S
U
S
 
2,830
2.2
0.5
0.0
 
694
0.3
0.1
0.0
 
10,101
4.8
1.2
0.0
 
7,653
9.5
3.7
0.0
 
S
S
U
S
 
28,684
2.9
1.1
0.1
 
S
S
U
S
 
12,157
1.0
0.4
0.0
 
118,466
10.1
2.4
0.2
 
22,935
3.0
1.2
0.1
 
41,022
5.3
1.3
0.1
 
S
S
U
S
 
345
1.4
0.3
0.0
 
443,177
2.1
0.8
1.6
 
512,280
2.5
0.6
0.7
 
5,751
1.4
0.6
0.0
 
11,826
2.9
0.7
0.0
 
S
S
U
S
 
S
S
U
S
 
3,002
2.1
0.8
0.0
 
4,424
3.1
0.7
0.0
 
2,956
0.9
0.4
0.0
 
15,621
5.0
1.2
0.0
 
510,602
2.1
0.8
1.8
 
2,710,264
11.4
2.7
3.5
 
5,846
0.6
0.2
0.0
 
74,038
7.0
1.7
0.1
 
S
S
U
S
 
9,610
3.2
0.8
0.0
 
54
0.2
0.1
0.0
 
S
S
U
S
 
39,601
2.1
0.8
0.1
 
20,991
1.1
0.3
0.0
 
31,830
2.8
1.1
0.1
 
46,371
4.1
1.0
0.1
 
S
S
U
S
 
3,751
4.8
1.1
0.0
 
2,943
0.7
0.3
0.0
 
31,193
6.9
1.6
0.0
 
375,258
2.7
1.1
1.3
 
408,517
2.9
0.7
0.5
 
2,123
0.5
0.2
0.0
 
18,043
4.0
1.0
0.0
 
226
0.2
0.1
0.0
 
S
S
U
S
 
23,213
1.3
0.5
0.1
 
74,649
4.0
1.0
0.1
 
22,231
3.8
1.5
0.1
 
26,910
4.6
1.1
0.0
 
7,549
1.1
0.4
0.0
 
37,915
5.3
1.3
0.0
 
162,133
4.7
1.8
0.6
 
94,615
2.7
0.6
0.1
 
943
0.1
0.1
0.0
 
S
S
U
S
 
7,117
1.7
0.7
0.0
 
51,382
12.6
3.0
0.1
 
29,944
3.4
1.3
0.1
 
33,058
3.8
0.9
0.0
 
79,475
1.2
0.5
0.3
 
380,383
5.5
1.3
0.5
 
S
S
U
S
 
4,507
2.4
0.6
0.0
 
1,645
1.1
0.4
0.0
 
S
S
U
S
 
99,387
3.3
1.3
0.3
 
168,420
5.6
1.3
0.2
 
S
S
U
S
 
18,537
10.6
2.5
0.0
 
S
S
U
S
 
410
0.8
0.2
0.0
 
3,386
1.8
0.7
0.0
 
7,786
4.2
1.0
0.0
 
35,007
5.3
2.1
0.1
 
80,815
12.1
2.9
0.1
 
10,167
7.1
2.8
0.0
 
6,067
4.3
1.0
0.0
 
124
0.5
0.2
0.0
 
S
S
U
S
 
5,745
1.3
0.5
0.0
 
44,835
9.8
2.3
0.1
 
100,656
3.2
1.2
0.4
 
89,370
2.8
0.7
0.1
 
S
S
U
S
 
9,471
4.5
1.1
0.0
 
27,041
2.5
1.0
0.1
 
20,584
1.9
0.4
0.0
 
3,157
1.8
0.7
0.0
 
3,357
1.9
0.5
0.0
 
S
S
U
S
 
9,790
5.2
1.2
0.0
 
4,802
2.6
1.0
0.0
 
13,357
7.1
1.7
0.0
 
32,884
1.8
0.7
0.1
 
63,186
3.5
0.8
0.1
 
S
S
U
S
 
S
S
U
S
 
S
S
U
S
 
S
S
U
S
 
4,076
0.7
0.3
0.0
 
36,151
6.3
1.5
0.0
 
3,445
1.4
0.5
0.0
 
S
S
U
S
 
1,954
0.2
0.1
0.0
 
62,483
6.2
1.5
0.1
 
S
S
U
S
 
8,140
3.5
0.8
0.0
 
301,910
2.6
1.0
1.1
 
417,478
3.5
0.8
0.5
 
6,358
1.7
0.7
0.0
 
14,720
4.0
0.9
0.0
 
7,901
0.9
0.3
0.0
 
58,289
6.5
1.5
0.1
 
1,434
0.6
0.2
0.0
 
S
S
U
S
 
S
S
U
S
 
937
2.8
0.7
0.0
 
288
0.4
0.2
0.0
 
S
S
U
S
 
813
0.7
0.3
0.0
 
S
S
U
S
 
S
S
U
S
 
S
S
U
S
 
1,378,756
1.4
0.6
4.8
 
9,668,036
10.0
2.4
12.7
 
133,689
2.5
1.0
0.5
 
139,652
2.6
0.6
0.2
 
S
S
U
S
 
S
S
U
S
 
6,649
2.6
1.0
0.0
 
7,922
3.1
0.7
0.0
 
23
0.1
0.0
0.0
 
2,762
9.6
2.3
0.0
 
14,733
1.1
0.4
0.1
 
16,560
1.3
0.3
0.0
 
101,755
2.2
0.9
0.4
 
78,612
1.7
0.4
0.1
 
2,276,623
2.1
0.8
8.0
 
1,591,589
1.5
0.4
2.1
 
961
0.6
0.2
0.0
 
5,841
3.7
0.9
0.0
 
3,369
1.3
0.5
0.0
 
12,591
5.0
1.2
0.0
 
3,161
0.5
0.2
0.0
 
43,888
7.3
1.7
0.1
 
S
S
U
S
 
S
S
U
S
 
21,028
3.1
1.2
0.1
 
33,368
5.0
1.2
0.0
 
19,619
1.4
0.5
0.1
 
67,369
4.7
1.1
0.1
 
19,350
2.3
0.9
0.1
 
36,251
4.3
1.0
0.0
 
106,704
3.4
1.3
0.4
 
132,359
4.2
1.0
0.2
 
18,621
1.1
0.4
0.1
 
7,790
0.5
0.1
0.0
 
28,150
1.5
0.6
0.1
 
196,984
10.8
2.6
0.3
 
23,299
4.9
1.9
0.1
 
36,102
7.5
1.8
0.0
 
28,969
2.2
0.8
0.1
 
S
S
U
S
 
205,221
2.9
1.1
0.7
 
1,457,670
20.3
4.8
1.9
 
17,436
1.7
0.7
0.1
 
57,854
5.8
1.4
0.1
 
1,591
1.4
0.6
0.0
 
13,216
11.9
2.8
0.0
 
71,862
1.7
0.7
0.3
 
177,625
4.2
1.0
0.2
 
6,292
1.7
0.7
0.0
 
14,657
3.9
0.9
0.0
 
3,354
1.2
0.5
0.0
 
17,259
6.0
1.4
0.0
 
306,498
1.4
0.6
1.1
 
443,660
2.0
0.5
0.6
 
20,861
3.0
1.2
0.1
 
22,759
3.3
0.8
0.0
 
8,872
2.4
0.9
0.0
 
69,552
18.9
4.5
0.1
 
45,645
2.5
1.0
0.2
 
118,442
6.6
1.6
0.2
 
13,545
1.6
0.6
0.0
 
23,549
2.8
0.7
0.0
 
7,783
2.4
1.0
0.0
 
S
S
U
S
 
4,610
0.7
0.3
0.0
 
14,521
2.3
0.6
0.0
 
S
S
U
S
 
2,875
1.2
0.3
0.0
 
S
S
U
S
 
S
S
U
S
 
 
 
 
 
 
 
 
 
 
 
 
28,535,342
2.1
0.8
100.0
 
76,397,495
5.7
1.4
100.0
 
26,794,073
2.1
0.8
93.9
 
72,818,997
5.8
1.4
95.3
 
1,741,269
2.1
0.8
6.1
 
3,578,498
4.4
1.0
4.7
 
 
 
 
 
 
 
 
 
 
 
 
389,364,000
2.6
1.0
 
638,088,000
4.2
1.0
 
357,213,063
2.6
1.0
 
578,859,079
4.2
1.0
 
32,150,937
2.5
1.0
 
59,228,921
4.5
1.1
Source: Calculations by the Texas Regional Economic Analysis Project (TX-REAP)
with data provided by the U.S. Department of Commerce, Bureau of Economic Analysis
November 2023
REAP_PI_CA1600N_611100_610800_SA
 
   
Select an alternate year:
   
 
Real Estate and Rental and Leasing vs. Transportation and Warehousing
Earnings Structure by Region:
Texas, 2022
 
Real Estate and Rental and Leasing
 
Transportation and Warehousing
Metropolitan Statistical Areas
 
 
 
147,508
2.5
1.0
0.5
 
165,798
2.8
0.7
0.2
 
S
S
U
S
 
560,964
5.3
1.3
0.7
 
2,872,375
2.1
0.8
10.1
 
2,668,700
1.9
0.5
3.5
 
170,579
1.3
0.5
0.6
 
494,094
3.8
0.9
0.6
 
201,777
2.2
0.8
0.7
 
520,037
5.5
1.3
0.7
 
227,765
2.5
1.0
0.8
 
S
S
U
S
 
408,142
2.6
1.0
1.4
 
471,703
3.0
0.7
0.6
 
10,368,157
2.4
0.9
36.3
 
25,352,209
5.8
1.4
33.2
 
394,334
1.6
0.6
1.4
 
S
S
U
S
 
7,081,054
1.9
0.7
24.8
 
30,676,173
8.2
1.9
40.2
 
354,549
2.3
0.9
1.2
 
S
S
U
S
 
205,221
2.9
1.1
0.7
 
1,457,670
20.3
4.8
1.9
 
277,330
2.9
1.1
1.0
 
385,729
4.1
1.0
0.5
 
172,667
1.6
0.6
0.6
 
S
S
U
S
 
346,120
1.9
0.8
1.2
 
1,053,512
5.9
1.4
1.4
 
443,871
2.1
0.8
1.6
 
522,381
2.5
0.6
0.7
 
209,310
2.9
1.1
0.7
 
490,182
6.8
1.6
0.6
 
S
S
U
S
 
82,370
1.7
0.4
0.1
 
1,775,057
1.8
0.7
6.2
 
S
S
U
S
 
40,086
1.1
0.4
0.1
 
104,375
2.9
0.7
0.1
 
S
S
U
S
 
176,465
4.4
1.0
0.2
 
301,910
2.6
1.0
1.1
 
417,478
3.5
0.8
0.5
 
108,588
3.4
1.3
0.4
 
S
S
U
S
 
S
S
U
S
 
S
S
U
S
 
77,710
1.7
0.7
0.3
 
S
S
U
S
 
 
 
 
 
 
 
 
 
 
 
 
28,535,342
2.1
0.8
100.0
 
76,397,495
5.7
1.4
100.0
 
26,794,073
2.1
0.8
93.9
 
72,818,997
5.8
1.4
95.3
 
1,741,269
2.1
0.8
6.1
 
3,578,498
4.4
1.0
4.7
 
 
 
 
 
 
 
 
 
 
 
 
389,364,000
2.6
1.0
 
638,088,000
4.2
1.0
 
357,213,063
2.6
1.0
 
578,859,079
4.2
1.0
 
32,150,937
2.5
1.0
 
59,228,921
4.5
1.1
Source: Calculations by the Texas Regional Economic Analysis Project (TX-REAP)
with data provided by the U.S. Department of Commerce, Bureau of Economic Analysis
November 2023
REAP_PI_CA1600N_611100_610800_SB
 
   
Real* Earnings Growth by County
Growth Rates, 2022
Select a Year/Indicator:Growth RatesComponent Contributions
Real* Earnings Growth by County
View Distribution Totals as:Actual Percent
   
 
Real Estate and Rental and Leasing vs. Transportation and Warehousing
Texas Real* Earnings Growth Distribution by County:
Growth Rates, 2022
More
than
50%
50%
to
40%
40%
to
30%
30%
to
20%
20%
to
10%
10%
to
0%
0%
or
Below
Suppressed
or
Undefined
Total
Real Estate and Rental and Leasing
2
1
3
4
12
26
150
56
254
Transportation and Warehousing
5
2
8
12
45
71
34
77
254
 
   
Select an alternate year:
   
 
Real Estate and Rental and Leasing vs. Transportation and Warehousing
Real* Earnings Growth by County:
Texas, 2022
 
Real Estate and Rental and Leasing
 
Transportation and Warehousing
 
 
 
7.3
0.1
11.8
5.6
 
0.6
0.1
-2.6
-11.4
 
15.3
0.3
19.8
13.6
 
7.3
0.4
4.1
-4.7
 
-1.7
0.0
2.8
-3.5
 
-8.1
-0.3
-11.2
-20.1
 
-10.4
-0.7
-5.9
-12.1
 
N
N
N
N
 
N
N
N
N
 
-2.7
-0.1
-5.9
-14.7
 
N
N
N
N
 
N
N
N
N
 
11.0
0.3
15.5
9.3
 
85.5
4.2
82.3
73.5
 
-8.0
-0.3
-3.5
-9.7
 
16.0
0.9
12.8
4.0
 
N
N
N
N
 
7.2
0.4
4.0
-4.8
 
13.1
0.1
17.6
11.4
 
20.4
0.7
17.2
8.4
 
-6.1
-0.1
-1.6
-7.8
 
12.4
0.3
9.3
0.4
 
N
N
N
N
 
N
N
N
N
 
-4.3
-0.1
0.2
-6.0
 
13.7
0.2
10.5
1.7
 
-6.2
-0.1
-1.7
-8.0
 
0.0
0.0
-3.2
-12.0
 
6.7
0.1
11.2
4.9
 
16.4
0.6
13.3
4.4
 
-5.2
-0.2
-0.7
-6.9
 
4.9
0.2
1.7
-7.1
 
-12.3
-0.1
-7.7
-14.0
 
N
N
N
N
 
-12.0
-0.3
-7.5
-13.7
 
35.1
1.0
31.9
23.0
 
-1.6
0.0
2.9
-3.3
 
-6.1
-0.2
-9.3
-18.1
 
0.8
0.0
5.3
-0.9
 
1.2
0.0
-2.0
-10.8
 
-5.1
-0.1
-0.6
-6.8
 
N
N
N
N
 
-5.9
-0.1
-1.4
-7.6
 
-8.1
-0.1
-11.3
-20.1
 
-27.9
-0.1
-23.4
-29.6
 
7.2
0.0
4.0
-4.8
 
N
N
N
N
 
26.9
0.6
23.7
14.8
 
-11.2
-0.2
-6.7
-12.9
 
-11.7
-0.3
-14.9
-23.7
 
15.9
0.2
20.4
14.1
 
3.1
0.3
-0.1
-9.0
 
-11.3
-0.6
-6.8
-13.1
 
N
N
N
N
 
-10.7
-0.3
-6.2
-12.4
 
-4.7
-0.5
-7.9
-16.7
 
4.8
0.0
9.3
3.0
 
41.4
0.6
38.2
29.3
 
1.8
0.1
6.3
0.0
 
20.4
1.0
17.3
8.4
 
-6.4
-0.1
-1.9
-8.1
 
11.6
0.6
8.4
-0.4
 
-13.5
-0.6
-9.0
-15.3
 
42.2
0.7
39.0
30.1
 
-30.6
0.0
-26.1
-32.4
 
-0.6
0.0
-3.8
-12.7
 
-3.8
-0.1
0.7
-5.5
 
3.4
0.2
0.2
-8.6
 
N
N
N
N
 
-0.7
0.0
-3.9
-12.8
 
-12.8
-0.2
-8.3
-14.5
 
11.6
1.6
8.4
-0.4
 
1.0
0.0
5.5
-0.7
 
14.0
0.2
10.8
1.9
 
4.9
0.0
9.4
3.2
 
N
N
N
N
 
N
N
N
N
 
N
N
N
N
 
-12.3
0.0
-7.8
-14.0
 
N
N
N
N
 
N
N
N
N
 
N
N
N
N
 
37.0
1.7
41.5
35.3
 
N
N
N
N
 
9.0
0.2
13.5
7.3
 
22.7
0.2
19.5
10.6
 
N
N
N
N
 
N
N
N
N
 
-18.4
-0.5
-13.9
-20.1
 
7.7
0.5
4.5
-4.3
 
-9.2
-0.3
-4.7
-11.0
 
12.0
0.6
8.8
0.0
 
-14.6
-0.2
-10.1
-16.4
 
37.2
2.3
34.0
25.1
 
-19.4
0.0
-14.9
-21.1
 
N
N
N
N
 
-9.7
-0.6
-5.2
-11.4
 
0.7
0.0
-2.5
-11.3
 
-25.8
-0.8
-21.2
-27.5
 
-13.4
-0.2
-16.6
-25.4
 
N
N
N
N
 
N
N
N
N
 
-28.0
-2.8
-23.5
-29.8
 
27.0
2.8
23.8
15.0
 
10.8
0.1
15.3
9.1
 
2.4
0.4
-0.8
-9.6
 
N
N
N
N
 
N
N
N
N
 
N
N
N
N
 
N
N
N
N
 
-11.5
-0.2
-7.0
-13.2
 
N
N
N
N
 
5.7
0.2
10.2
4.0
 
13.6
0.6
10.4
1.6
 
-4.4
0.0
0.2
-6.1
 
4.8
0.1
1.6
-7.2
 
-4.5
0.0
0.0
-6.3
 
1.1
0.0
-2.1
-10.9
 
N
N
N
N
 
N
N
N
N
 
0.3
0.0
4.8
-1.5
 
14.5
0.9
11.3
2.4
 
47.4
2.2
51.9
45.7
 
2.1
0.1
-1.1
-9.9
 
-12.5
-0.1
-8.0
-14.2
 
5.6
0.1
2.4
-6.4
 
-13.9
-0.5
-9.4
-15.7
 
-3.0
-0.1
-6.2
-15.0
 
N
N
N
N
 
37.4
0.9
34.2
25.4
 
-17.8
0.0
-13.3
-19.5
 
0.3
0.0
-2.9
-11.7
 
-6.7
-0.2
-2.2
-8.4
 
29.9
1.5
26.7
17.8
 
25.6
0.6
30.1
23.9
 
15.3
1.0
12.2
3.3
 
N
N
N
N
 
N
N
N
N
 
13.5
0.1
18.1
11.8
 
5.2
0.4
2.0
-6.8
 
-2.3
0.0
2.2
-4.0
 
10.0
0.6
6.8
-2.0
 
-9.1
-0.3
-4.6
-10.8
 
-1.3
0.0
-4.5
-13.3
 
N
N
N
N
 
N
N
N
N
 
-8.1
-0.2
-3.6
-9.8
 
6.3
0.1
3.1
-5.7
 
-19.2
-0.8
-14.7
-21.0
 
N
N
N
N
 
N
N
N
N
 
6.0
0.3
2.8
-6.1
 
N
N
N
N
 
6.8
0.2
3.6
-5.2
 
-12.5
0.0
-8.0
-14.3
 
N
N
N
N
 
0.7
0.0
5.2
-1.0
 
26.8
0.9
23.6
14.8
 
N
N
N
N
 
N
N
N
N
 
-13.4
-0.3
-8.9
-15.1
 
7.1
0.6
3.9
-4.9
 
-18.8
-0.4
-14.3
-20.5
 
-0.5
0.0
-3.7
-12.5
 
-14.4
-0.2
-9.9
-16.2
 
17.5
1.1
14.3
5.5
 
-7.4
-0.1
-2.9
-9.2
 
6.4
0.2
3.2
-5.6
 
N
N
N
N
 
N
N
N
N
 
-13.7
-1.3
-9.2
-15.5
 
N
N
N
N
 
N
N
N
N
 
N
N
N
N
 
-14.1
-0.3
-9.6
-15.8
 
N
N
N
N
 
-9.9
0.0
-5.4
-11.6
 
12.6
0.5
9.4
0.6
 
-7.3
-0.1
-2.8
-9.0
 
-2.5
-0.1
-5.6
-14.5
 
-9.9
-0.1
-5.3
-11.6
 
6.1
0.2
2.9
-6.0
 
0.3
0.0
4.8
-1.4
 
13.3
0.6
10.1
1.2
 
1.6
0.1
6.1
-0.1
 
18.4
0.7
15.3
6.4
 
9.5
0.3
14.0
7.8
 
9.3
0.7
6.2
-2.7
 
-9.5
-0.2
-5.0
-11.3
 
-1.9
-0.2
-5.0
-13.9
 
-12.4
-0.1
-7.9
-14.2
 
N
N
N
N
 
N
N
N
N
 
N
N
N
N
 
-15.5
0.0
-11.0
-17.2
 
11.9
0.4
8.7
-0.1
 
N
N
N
N
 
10.6
0.5
7.4
-1.5
 
-8.1
-0.1
-3.6
-9.8
 
2.1
0.1
-1.0
-9.9
 
-1.1
0.0
3.4
-2.9
 
14.0
1.1
10.8
2.0
 
2.4
0.1
6.9
0.7
 
2.1
0.1
-1.1
-9.9
 
N
N
N
N
 
22.9
0.8
19.7
10.9
 
N
N
N
N
 
5.1
0.1
1.9
-6.9
 
-3.0
-0.1
1.5
-4.7
 
30.3
1.8
27.1
18.3
 
-10.5
-0.2
-6.0
-12.2
 
N
N
N
N
 
-8.3
-0.2
-3.8
-10.0
 
7.0
0.2
3.8
-5.0
 
-7.4
-0.2
-2.9
-9.1
 
10.0
0.5
6.8
-2.0
 
-1.8
0.0
2.7
-3.6
 
31.4
1.3
28.2
19.4
 
-10.9
-0.2
-6.4
-12.6
 
1.0
0.0
-2.2
-11.0
 
-9.5
-0.5
-5.0
-11.3
 
3.8
0.1
0.7
-8.2
 
21.4
0.2
25.9
19.7
 
1.7
0.1
-1.5
-10.3
 
-2.0
0.0
2.5
-3.7
 
N
N
N
N
 
-13.2
-0.2
-8.7
-14.9
 
16.7
0.3
13.6
4.7
 
-13.6
0.0
-9.1
-15.4
 
N
N
N
N
 
5.1
0.1
9.6
3.4
 
11.4
0.2
8.2
-0.6
 
-7.5
-0.1
-3.0
-9.3
 
3.3
0.1
0.1
-8.7
 
N
N
N
N
 
17.3
0.5
14.1
5.3
 
N
N
N
N
 
4.0
0.2
0.8
-8.0
 
-19.5
-0.2
-15.0
-21.2
 
N
N
N
N
 
5.0
0.1
9.5
3.3
 
N
N
N
N
 
N
N
N
N
 
12.2
0.1
9.0
0.2
 
10.4
0.1
14.9
8.6
 
1.5
0.1
-1.7
-10.5
 
N
N
N
N
 
N
N
N
N
 
8.0
0.2
12.5
6.2
 
5.3
0.1
2.1
-6.8
 
-6.8
-0.2
-2.3
-8.6
 
7.5
0.5
4.3
-4.5
 
37.3
0.2
41.8
35.6
 
-1.8
-0.1
-5.0
-13.8
 
-19.2
-0.6
-14.7
-20.9
 
-4.5
-0.3
-7.6
-16.5
 
-4.7
-0.1
-0.2
-6.4
 
16.7
2.3
13.5
4.6
 
-9.5
-0.5
-5.0
-11.2
 
N
N
N
N
 
-12.1
0.0
-7.6
-13.8
 
-6.1
0.0
-9.3
-18.1
 
N
N
N
N
 
34.4
0.3
31.2
22.3
 
-11.6
-0.9
-7.1
-13.3
 
N
N
N
N
 
-21.1
-0.8
-16.6
-22.9
 
N
N
N
N
 
-12.5
-0.1
-8.0
-14.2
 
228.8
0.0
225.6
216.7
 
N
N
N
N
 
N
N
N
N
 
16.0
0.1
20.5
14.3
 
-6.5
-0.1
-9.7
-18.6
 
N
N
N
N
 
N
N
N
N
 
3.2
0.0
7.7
1.4
 
9.4
0.2
6.3
-2.6
 
-11.7
-0.1
-7.2
-13.5
 
6.5
0.2
3.3
-5.6
 
-9.9
-0.5
-5.4
-11.6
 
N
N
N
N
 
N
N
N
N
 
22.7
0.8
19.5
10.7
 
-8.3
-0.3
-3.8
-10.0
 
N
N
N
N
 
-8.6
-0.1
-4.1
-10.3
 
N
N
N
N
 
-1.3
0.0
3.2
-3.0
 
16.1
0.4
12.9
4.1
 
-6.1
-0.1
-1.6
-7.8
 
5.5
0.4
2.3
-6.5
 
-17.9
-0.1
-13.4
-19.7
 
11.8
0.1
8.6
-0.3
 
N
N
N
N
 
18.8
2.0
15.6
6.8
 
-0.4
0.0
4.1
-2.1
 
-18.6
-2.2
-21.7
-30.6
 
-10.7
-0.8
-6.1
-12.4
 
N
N
N
N
 
-21.7
0.0
-17.2
-23.5
 
N
N
N
N
 
-3.3
-0.1
1.3
-5.0
 
9.2
0.3
6.0
-2.8
 
N
N
N
N
 
N
N
N
N
 
-13.7
-0.2
-9.2
-15.4
 
N
N
N
N
 
-3.4
-0.1
1.1
-5.1
 
16.7
0.4
13.6
4.7
 
N
N
N
N
 
N
N
N
N
 
3.4
0.0
7.9
1.7
 
N
N
N
N
 
N
N
N
N
 
N
N
N
N
 
-25.4
-0.1
-20.9
-27.1
 
-7.9
-0.4
-11.1
-19.9
 
-21.8
-2.4
-17.3
-23.5
 
N
N
N
N
 
-4.4
-0.1
0.1
-6.1
 
N
N
N
N
 
-6.0
-0.1
-1.5
-7.7
 
14.3
1.3
11.1
2.3
 
-10.6
-0.3
-6.1
-12.3
 
5.1
0.2
1.9
-6.9
 
N
N
N
N
 
62.8
0.5
59.7
50.8
 
1.7
0.0
6.2
0.0
 
3.5
0.1
0.3
-8.6
 
-9.7
-0.2
-5.2
-11.4
 
12.7
0.3
9.5
0.7
 
N
N
N
N
 
N
N
N
N
 
28.3
0.4
32.9
26.6
 
-1.5
0.0
-4.7
-13.5
 
-0.1
0.0
4.4
-1.8
 
10.0
0.4
6.8
-2.0
 
7.7
0.2
12.2
6.0
 
32.8
3.0
29.6
20.8
 
-15.7
-0.1
-11.2
-17.5
 
6.6
0.4
3.5
-5.4
 
N
N
N
N
 
-4.9
-0.2
-8.1
-16.9
 
-12.5
0.0
-8.0
-14.3
 
N
N
N
N
 
-9.6
-0.2
-5.1
-11.4
 
0.4
0.0
-2.8
-11.6
 
-5.7
-0.2
-1.2
-7.4
 
5.4
0.2
2.2
-6.6
 
N
N
N
N
 
10.5
0.4
7.3
-1.6
 
62.6
0.2
67.1
60.9
 
6.0
0.3
2.8
-6.1
 
-1.6
0.0
2.9
-3.3
 
0.3
0.0
-2.9
-11.7
 
-19.2
-0.1
-14.7
-21.0
 
N
N
N
N
 
-12.3
0.0
-7.8
-14.0
 
N
N
N
N
 
-0.5
0.0
4.0
-2.2
 
11.8
0.4
8.6
-0.3
 
-20.9
-1.0
-16.4
-22.6
 
5.9
0.3
2.7
-6.2
 
-11.1
-0.1
-6.6
-12.9
 
-6.7
-0.4
-9.8
-18.7
 
-6.3
-0.3
-1.8
-8.0
 
-16.2
-0.6
-19.4
-28.2
 
-28.7
-0.1
-24.2
-30.4
 
N
N
N
N
 
-17.7
-0.4
-13.2
-19.4
 
9.3
1.1
6.1
-2.7
 
6.8
0.2
11.3
5.1
 
9.4
0.3
6.2
-2.6
 
-10.9
-0.1
-6.4
-12.6
 
4.6
0.2
1.4
-7.4
 
N
N
N
N
 
3.5
0.1
0.3
-8.6
 
-13.9
-0.2
-9.4
-15.6
 
N
N
N
N
 
-8.8
-0.3
-4.3
-10.5
 
N
N
N
N
 
N
N
N
N
 
0.6
0.1
-2.6
-11.4
 
N
N
N
N
 
17.4
0.1
14.2
5.4
 
-7.9
-0.1
-3.4
-9.6
 
8.0
0.3
4.8
-4.1
 
11.2
0.5
15.7
9.5
 
14.2
1.6
11.1
2.2
 
71.1
2.8
75.6
69.4
 
-6.0
-0.3
-9.2
-18.0
 
-17.4
-0.1
-12.9
-19.1
 
N
N
N
N
 
-3.3
0.0
1.2
-5.1
 
4.6
0.5
1.4
-7.4
 
-9.8
-0.4
-5.3
-11.6
 
N
N
N
N
 
N
N
N
N
 
19.1
0.7
16.0
7.1
 
-4.7
-0.1
-0.2
-6.5
 
-4.0
-0.1
-7.2
-16.0
 
-11.6
-0.2
-7.1
-13.3
 
73.4
0.8
70.3
61.4
 
N
N
N
N
 
8.4
0.5
5.2
-3.6
 
-16.8
-0.5
-12.3
-18.5
 
21.2
1.2
18.0
9.1
 
-1.0
0.0
3.5
-2.7
 
20.7
0.6
17.5
8.7
 
N
N
N
N
 
N
N
N
N
 
N
N
N
N
 
N
N
N
N
 
-1.4
0.0
3.1
-3.1
 
62.6
2.6
59.4
50.6
 
-18.4
-0.3
-13.9
-20.1
 
N
N
N
N
 
-15.5
0.0
-11.0
-17.2
 
20.3
1.3
17.1
8.2
 
N
N
N
N
 
N
N
N
N
 
-6.3
-0.2
-1.8
-8.1
 
0.1
0.0
-3.1
-11.9
 
-7.2
-0.1
-2.7
-8.9
 
-0.2
0.0
-3.3
-12.2
 
N
N
N
N
 
12.9
0.7
9.7
0.9
 
-8.0
-0.1
-3.5
-9.7
 
N
N
N
N
 
N
N
N
N
 
-13.9
-0.4
-17.1
-25.9
 
-12.2
-0.1
-7.7
-13.9
 
N
N
N
N
 
-14.4
-0.1
-9.9
-16.1
 
N
N
N
N
 
N
N
N
N
 
N
N
N
N
 
3.6
0.1
8.1
1.9
 
4.0
0.4
0.9
-8.0
 
-5.0
-0.1
-0.5
-6.8
 
2.5
0.1
-0.6
-9.5
 
N
N
N
N
 
N
N
N
N
 
-5.6
-0.1
-1.1
-7.3
 
N
N
N
N
 
-13.6
0.0
-9.1
-15.3
 
N
N
N
N
 
-2.9
0.0
1.6
-4.6
 
-6.7
-0.1
-9.9
-18.7
 
-7.4
-0.2
-2.9
-9.1
 
6.0
0.1
2.8
-6.0
 
11.2
0.2
15.7
9.5
 
15.2
0.2
12.0
3.2
 
0.3
0.0
4.8
-1.4
 
3.4
0.1
0.2
-8.7
 
-10.8
-0.2
-6.3
-12.6
 
14.9
0.6
11.8
2.9
 
-19.8
-0.1
-15.3
-21.5
 
35.4
2.0
32.2
23.4
 
N
N
N
N
 
N
N
N
N
 
-12.6
-0.4
-8.1
-14.3
 
2.3
0.1
-0.9
-9.7
 
-10.9
-0.2
-6.4
-12.7
 
-0.5
0.0
-3.7
-12.5
 
-8.9
-0.2
-4.4
-10.7
 
13.6
0.5
10.4
1.6
 
-6.1
-0.2
-1.6
-7.8
 
5.5
0.2
2.3
-6.5
 
-10.2
-0.1
-5.6
-11.9
 
-23.5
-0.1
-26.7
-35.5
 
-0.9
0.0
3.6
-2.6
 
17.9
1.7
14.8
5.9
 
39.6
1.5
44.1
37.9
 
2.1
0.2
-1.1
-9.9
 
-2.7
-0.1
1.8
-4.4
 
N
N
N
N
 
-1.4
0.0
3.2
-3.1
 
6.4
1.2
3.2
-5.6
 
-11.1
-0.2
-6.6
-12.8
 
-3.2
-0.2
-6.4
-15.2
 
-8.3
-0.1
-3.8
-10.0
 
7.9
0.7
4.7
-4.1
 
-6.1
-0.1
-1.6
-7.8
 
-4.3
-0.2
-7.5
-16.4
 
-5.3
-0.1
-0.8
-7.0
 
8.3
0.3
5.1
-3.8
 
-11.7
-0.1
-7.2
-13.4
 
10.6
0.5
7.4
-1.5
 
-4.3
-0.1
0.2
-6.0
 
10.7
0.2
7.5
-1.3
 
-1.7
-0.1
2.8
-3.4
 
17.5
0.5
14.3
5.4
 
13.6
0.3
18.2
11.9
 
0.3
0.1
-2.9
-11.7
 
1.1
0.0
5.6
-0.7
 
N
N
N
N
 
-8.7
-0.2
-4.2
-10.5
 
15.8
0.4
12.6
3.8
 
15.0
0.3
19.5
13.3
 
N
N
N
N
 
21.3
0.1
25.8
19.6
 
6.9
0.2
3.7
-5.1
 
N
N
N
N
 
-15.9
-0.2
-19.1
-27.9
 
N
N
N
N
 
N
N
N
N
 
 
 
 
 
 
 
 
 
 
 
 
1.7
0.0
6.2
0.0
 
12.0
0.6
8.8
0.0
 
2.2
0.0
6.7
0.5
 
12.3
0.7
9.1
0.3
 
-5.3
-0.1
-0.8
-7.1
 
7.1
0.3
3.9
-5.0
 
 
 
 
 
 
 
 
 
 
 
 
-4.5
-0.1
0.0
 
3.2
0.1
0.0
 
-4.9
-0.1
-0.4
 
3.5
0.1
0.3
 
0.6
0.0
5.1
 
0.5
0.0
-2.6
Source: Calculations by the Texas Regional Economic Analysis Project (TX-REAP)
with data provided by the U.S. Department of Commerce, Bureau of Economic Analysis
November 2023
REAP_PI_CA1600N_611100_610800_GA
 
   
Select an alternate year:
   
 
Real Estate and Rental and Leasing vs. Transportation and Warehousing
Real* Earnings Growth by Region:
Texas, 2022
 
Real Estate and Rental and Leasing
 
Transportation and Warehousing
Metropolitan Statistical Areas
 
 
 
-4.0
-0.1
0.5
-5.7
 
3.3
0.1
0.1
-8.7
 
N
N
N
N
 
N
N
N
N
 
7.7
0.2
12.2
5.9
 
16.2
0.3
13.0
4.2
 
7.6
0.1
12.1
5.9
 
3.0
0.1
-0.2
-9.0
 
-6.4
-0.1
-1.9
-8.1
 
11.6
0.6
8.4
-0.4
 
-4.6
-0.1
-0.1
-6.4
 
N
N
N
N
 
-1.5
0.0
3.0
-3.3
 
2.6
0.1
-0.6
-9.4
 
4.9
0.1
9.5
3.2
 
N
N
N
N
 
-2.3
0.0
2.2
-4.0
 
N
N
N
N
 
-0.7
0.0
3.8
-2.4
 
15.5
1.1
12.3
3.5
 
-8.4
-0.2
-3.9
-10.1
 
N
N
N
N
 
-1.4
0.0
3.2
-3.1
 
6.4
1.2
3.2
-5.6
 
-0.2
0.0
4.3
-1.9
 
12.7
0.5
9.5
0.7
 
-3.4
-0.1
1.1
-5.1
 
N
N
N
N
 
-7.4
-0.2
-2.9
-9.1
 
10.0
0.5
6.8
-2.0
 
1.7
0.0
6.2
0.0
 
3.2
0.1
0.0
-8.8
 
25.6
0.6
30.1
23.9
 
15.3
1.0
12.2
3.3
 
N
N
N
N
 
6.1
0.1
2.9
-5.9
 
3.9
0.1
8.4
2.2
 
N
N
N
N
 
-9.9
-0.1
-5.3
-11.6
 
6.1
0.2
2.9
-6.0
 
N
N
N
N
 
-2.5
-0.1
-5.7
-14.5
 
-6.3
-0.2
-1.8
-8.1
 
0.1
0.0
-3.1
-11.9
 
-6.2
-0.2
-1.7
-8.0
 
N
N
N
N
 
N
N
N
N
 
N
N
N
N
 
N
N
N
N
 
N
N
N
N
 
 
 
 
 
 
 
 
 
 
 
 
1.7
0.0
6.2
0.0
 
12.0
0.6
8.8
0.0
 
2.2
0.0
6.7
0.5
 
12.3
0.7
9.1
0.3
 
-5.3
-0.1
-0.8
-7.1
 
7.1
0.3
3.9
-5.0
 
 
 
 
 
 
 
 
 
 
 
 
-4.5
-0.1
0.0
 
3.2
0.1
0.0
 
-4.9
-0.1
-0.4
 
3.5
0.1
0.3
 
0.6
0.0
5.1
 
0.5
0.0
-2.6
Source: Calculations by the Texas Regional Economic Analysis Project (TX-REAP)
with data provided by the U.S. Department of Commerce, Bureau of Economic Analysis
November 2023
REAP_PI_CA1600N_611100_610800_GB
 
   
Additional Notes on Interpreting
Earnings for Texas
Earnings
The earnings by major industry estimates compiled by the Bureau of Economic Analysis (BEA) are by place of work, and are the sum of wage and salary disbursements (payrolls), supplements to wages and salaries, and proprietors' income. The earnings by industry data are expressed in thousands of current dollars ($1,000s). Unlike wage and salary disbursements, it should be noted that proprietors' income may be reported as negative for those years in which the net income of sole proprietors and partnerships are in the red for a particular sector. This is not an especially unusual occurrence in some relatively small economies where farm proprietorships are dominant. However, this may yield some somewhat unconventional results, such as an industry recording a negative share of total earnings.
Other/Suppressed Industries
For some areas, an industry category labeled "Other/Suppressed Industries" may appear in the table. It is not uncommon, especially for smaller areas, to encounter suppressed data for selected industries. Data are suppressed to avoid disclosure of confidential information regarding individual firms. Even though the concern for confidentiality may relate to only one industry, data for at least two must be suppressed as summing over the reported data and subtracting from the total yields data for the suppressed category. When suppressed data is encountered, it is reported in the "Other/Suppressed Industries" category.
Location Quotient
Location quotients help gauge the extent to which various industries are more or less concentrated locally when compared with the nation at large. If an industry's share of total earnings is the same as the national share, then its location quotient is equal to one. If an industry is concentrated in a region, its local employment share will be larger than the share nationally, and its location quotient will correspondingly be greater than one. Conversely, the location quotient for an industry not concentrated in the region will fall between zero and one.
Component Contribution
The component contribution isolates and records each industry's individual contribution to the total growth of earnings in Texas over 2022, and 2002-2022, respectively. When summed over all industries the component contribution will match Texas' TOTAL earnings growth rate.
Copyright © 2023. Pacific Northwest Regional Economic Analysis Project (PNREAP). All Rights Reserved.

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